Acerca del Curso

This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images.
You will:
- Understand how to build a convolutional neural network, including recent variations such as residual networks.
- Know how to apply convolutional networks to visual detection and recognition tasks.
- Know to use neural style transfer to generate art.
- Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data.
This is the fourth course of the Deep Learning Specialization....

Principales revisiones

AG

Jan 13, 2019

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Great course for kickoff into the world of CNN's. Gives a nice overview of existing architectures and certain applications of CNN's as well as giving some solid background in how they work internally.

RK

Sep 02, 2019

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This is very intensive and wonderful course on CNN. No other course in the MOOC world can be compared to this course's capability of simplifying complex concepts and visualizing them to get intuition.

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251 - 275 de 4,019 revisiones para Convolutional Neural Networks

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por Miroslav M

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Apr 24, 2019

I've gained very important knowledge for Image verification and recognition algorithms using ConvNet models. These models are used nowadays powering robots and self-driving cars. Thank you very much deeplearning.ai for this opportunity to get closer to finishing my new carrier journey.

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por Janzaib M

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May 06, 2018

Very very well designed homework. Gave me a really close feel of deep learning for computer vision. The great thing is, in this course you play with very very state of the ConvNet architechture. Thank you so much Professor Andrew NG and your team. A very big contribution you have done.

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por Huang C H

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Nov 24, 2017

Convolutional Neural Network are exciting to learn, but its concept can be quite abstract. However the materials are delivered progressively, and in a concise manner. The programming exercises are challenging. I hope there was more in-depth introduction to Tensorflow and Keras, though.

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por AKSHAY K C

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Mar 19, 2020

The course had a very clear outline starting from the basic fundamentals of CNN and progressing steadily towards the applications ranging from facial recognition to neural style transfer in the final week. Kudos to the instructor and his team for delivering such an outstanding course.

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por Feng W

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Mar 15, 2019

I have some problem doing week four programming assignment "Happy House Face Verification/Recognition". The pre-trained model "FRmodel" wouldn't be loaded (waiting for over half hour). I still managed to submit the assignment and passed the test without running out the correct result.

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por badreddine m

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Dec 24, 2017

it is my second courses in coursera after Machine learning by Andrew Ng and Stanford university, I'm very satisfied by the courses quality and encourage you to go further, I'm a follower of coursera courses and one day I will contribute to share more knowledge using coursera platform.

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por Sami

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Feb 15, 2018

i think that's the most important course for me, of course all of them, where very very useful, but being an undergraduate Robotics engineer, the most essential thing is to learn image processing and how to make your robot think and learn and detect object and learn from environment.

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por Wooshik K

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Feb 11, 2020

Thank you for the lecture contents and programming problems. I am quite sure that I have acquired much knowledge and it will be very helpful to solve my own problems. Also, it would be much more helpful if there are some comments on how to build filter coefficients or filter banks.

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por Sathiraju E

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Aug 05, 2019

Amazing course. A lot of knowledge packaged into one package. This has been the most useful course in the deeplearning.ai. Thank you Andrew and team. Lot's of interesting stuff and knowledge has been shared out here. Only the back propagation for CNN was missing but otherwise great.

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por Yernur N

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Jul 18, 2019

It is an essential course for those who wants to boost their general knowledge in the area of CNNs. It will give you a great foundation to build on your career and further learning. I struggled a bit with Keras, but I am planning on taking another course to learn this field further.

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por Matheesha A

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Jun 21, 2019

This is an excellent course to learn the concepts of Convolutional Neural Nets. The hands on experience by the weekly assignments were very helpful to understand the concepts. I strongly recommend this course for the students who are interested in learning CNNs. Thanks Prof. Andrew.

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por Ravi P B

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Apr 17, 2020

A very detailed and pleasing insight into the amazing world of Convolutional Neural Networks and as always Andrew Sir has been absolutely brilliant in the lectures.This course presents an in depth knowledge of the challenges and various technologies in the field of computer vision.

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por Xiaolong L

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Feb 05, 2020

Excellent course! The programing exercises are both realistic and let you build (toy version) of state of art CV system. Many reference to heavy weight papers in the domain in the course, which student who really want to get into DL and CV can read and further expand their horizon.

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por MADAN M

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Feb 22, 2018

I got thrilled by the lectures and its assignments. One thing that I would request is a lecture on how to use pre-computed models, in all the assignments we are using pre-computed models. Andrew explains why we should use them but in practice its seems little difficult to use them.

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por Shaelander C

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Dec 10, 2019

Very informative course . Professor Andrew Ng has done a great job of explaining most of the concepts of CNN. And Assignments are really good to apply what we learn in the lectures. Professor Andrew is the best professor I ever came across the style of his teaching is unmatchable.

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por Guoliang

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Apr 17, 2020

This is a very detailed introduction to ConvNet with descriptions of some modern ConvNet architect. Though I feel that if the programming assignment could be much better if we can implement some of these algorithms from scratch with efficient implementation (using Google Colab?).

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por Dave J

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Apr 06, 2020

The material is clearly explained by Andrew Ng in his calm yet enthusiastic style. Programming exercises are well structured and explained: if anything I find there's too much hand-holding but having got the basics, there's nothing to stop you experimenting further on your own.

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por Animesh S

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May 21, 2019

Great course, concisely conveys both techniques and advice for practical implementation of Neural Networks in Image recognition. Great for a person who is already familiar with the idea of Deep Learning and want to take it forward, and ties in perfectly with the specialisation.

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por Ali S

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Aug 10, 2018

This course is a perfect way to teach these high-level concepts. They made it easy, step by step, and practical. You can learn not only convolutional neural networks in both conceptual and practical way, but also a lot of tips and tricks about tensorflow, Keras and even python.

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por Shivdas P

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Jan 01, 2020

The course is well structured, especially the exercise where one has to code the complete CNN example. It gives good insights on how to use the frameworks such as TensorFlow and Keras. Feel comfortable in understanding the concepts around CNN and it's implementation using TF.

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por Gurubux G

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Aug 20, 2019

One of the toughest and most exciting Course I have completed on the internet. Thanks a ton Andrew! I wish I can work with Deeplearning Team someday, so that I can learn every week, every day and probably explore the deepest of the Learning ocean potential that the team holds

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por Gilad R

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Aug 13, 2019

I really liked the dive into academic literature combined with the wide view of CNNs across various applications. The programming exercises were very revealing and informative, although a little more guidance on TensorFlow technicalities would have helped accelerate learning.

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por Bernard O

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Oct 31, 2018

This is quite a challenging course. Critical lessons on convolutions are the biggest value to me on this segment of the course. Takes a lot of the mystery out of CNN, but need to work hard at it. A very rewarding experience but does come with a few tear-my-hair-out incidents.

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por Stephen V K

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May 17, 2019

The course does an very good job of explaining the concepts behind different types of neural networks, but the homework assignments pretty much only test these concepts. Students should not expect to gain any significant experience coding neural networks in keras/tensorflow.

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por Himanshu B

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Jul 17, 2018

This is must course for the ones who really want to move into deep learning and the most important part of Deep learning and machine learning. So much informative and the best part is practical implementation where learning is so much great and informative with instructions.